Literature DB >> 11483182

Neural dynamics of motion integration and segmentation within and across apertures.

S Grossberg1, E Mingolla, L Viswanathan.   

Abstract

A neural model is developed of how motion integration and segmentation processes, both within and across apertures, compute global motion percepts. Figure-ground properties, such as occlusion, influence which motion signals determine the percept. For visible apertures, a line's terminators do not specify true line motion. For invisible apertures, a line's intrinsic terminators create veridical feature-tracking signals. Sparse feature-tracking signals can be amplified before they propagate across position and are integrated with ambiguous motion signals within line interiors. This integration process determines the global percept. It is the result of several processing stages: directional transient cells respond to image transients and input to a directional short-range filter that selectively boosts feature-tracking signals with the help of competitive signals. Then, a long-range filter inputs to directional cells that pool signals over multiple orientations, opposite contrast polarities, and depths. This all happens no later than cortical area MT. The directional cells activate a directional grouping network, proposed to occur within cortical area MST, within which directions compete to determine a local winner. Enhanced feature-tracking signals typically win over ambiguous motion signals. Model MST cells that encode the winning direction feed back to model MT cells, where they boost directionally consistent cell activities and suppress inconsistent activities over the spatial region to which they project. This feedback accomplishes directional and depthful motion capture within that region. Model simulations include the barberpole illusion, motion capture, the spotted barberpole, the triple barberpole, the occluded translating square illusion, motion transparency and the chopsticks illusion. Qualitative explanations of illusory contours from translating terminators and plaid adaptation are also given.

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Year:  2001        PMID: 11483182     DOI: 10.1016/s0042-6989(01)00131-6

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  20 in total

1.  Motion-based prediction is sufficient to solve the aperture problem.

Authors:  Laurent U Perrinet; Guillaume S Masson
Journal:  Neural Comput       Date:  2012-06-26       Impact factor: 2.026

2.  Binocular fusion and invariant category learning due to predictive remapping during scanning of a depthful scene with eye movements.

Authors:  Stephen Grossberg; Karthik Srinivasan; Arash Yazdanbakhsh
Journal:  Front Psychol       Date:  2015-01-14

3.  Low-level sensory plasticity during task-irrelevant perceptual learning: evidence from conventional and double training procedures.

Authors:  Praveen K Pilly; Stephen Grossberg; Aaron R Seitz
Journal:  Vision Res       Date:  2009-10-01       Impact factor: 1.886

4.  Neural dynamics of object-based multifocal visual spatial attention and priming: object cueing, useful-field-of-view, and crowding.

Authors:  Nicholas C Foley; Stephen Grossberg; Ennio Mingolla
Journal:  Cogn Psychol       Date:  2012-03-14       Impact factor: 3.468

5.  Bifurcation analysis applied to a model of motion integration with a multistable stimulus.

Authors:  James Rankin; Emilien Tlapale; Romain Veltz; Olivier Faugeras; Pierre Kornprobst
Journal:  J Comput Neurosci       Date:  2012-07-03       Impact factor: 1.621

6.  Representation of motion onset and offset in an augmented Barlow-Levick model of motion detection.

Authors:  Timothy Barnes; Ennio Mingolla
Journal:  J Comput Neurosci       Date:  2012-04-13       Impact factor: 1.621

7.  Peeling plaids apart: context counteracts cross-orientation contrast masking.

Authors:  Elliot Freeman; Preeti Verghese
Journal:  PLoS One       Date:  2009-12-02       Impact factor: 3.240

8.  What a difference a parameter makes: a psychophysical comparison of random dot motion algorithms.

Authors:  Praveen K Pilly; Aaron R Seitz
Journal:  Vision Res       Date:  2009-03-29       Impact factor: 1.886

9.  Desirability, availability, credit assignment, category learning, and attention: Cognitive-emotional and working memory dynamics of orbitofrontal, ventrolateral, and dorsolateral prefrontal cortices.

Authors:  Stephen Grossberg
Journal:  Brain Neurosci Adv       Date:  2018-05-08

10.  A Canonical Laminar Neocortical Circuit Whose Bottom-Up, Horizontal, and Top-Down Pathways Control Attention, Learning, and Prediction.

Authors:  Stephen Grossberg
Journal:  Front Syst Neurosci       Date:  2021-04-23
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